Senior Applied Scientist, Personalization
Are you a scientist interested in pushing the state of the art in recommendations and ranking? Are you interested in working on novel ideas that can positively impact millions of Amazon customers?
Do you wish you had access to large datasets? Are you passionate about publishing your work at conferences? Answer yes to any of these questions and you will be a great fit for our team at Amazon.
Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers.
We are building ML solutions to rank content on new shopping experiences on Amazon that inspire customers to find engaging multi-modal content (videos, images, reviews) related to their interests.
Amazon’s internal surveys regularly recognize us as one of the best organizations to work for in the company, with visible high-impact work, respectful work-life balance, and continual opportunity to learn and grow.
As a Senior Applied Scientist in our team, you will be working on cutting edge ways to help customers find the right products and content on their shopping journey.
You will lead the development of novel algorithms in areas such as deep learning and reinforcement learning while building scalable industrial systems.
As a member of a team of talented engineers and ML scientists, you will have a unique opportunity to help design and build infrastructure that accesses terabytes of data to produce and deliver models with low latency and high reliability.
We are building the next generation ML system that powers the biggest internet retailer on earth, and we hope you will join us!
Key job responsibilities
- Adopt or invent new machine learning techniques in the realm of real-world ranking, recommendation and large language models.
- Define and drive the team's science vision to provide step-change improvements to customer & business problems.
- Be technically fearless and with a passion for building scalable science and engineering solutions.
- Serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).
- Participate in organizational planning, hiring, mentorship and leadership development.
- Publish results at peer-reviewed conferences / journals.
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